ChatGPT, DALL-E, Stable Diffusion and other generative AI have rapidly captivated the public. They provide new, easy ways, to create new content based on AI models that have been trained on large, public data sets. How does this technology work? What does it mean for society? In this podcast we discuss the technology behind generative AI, some of the potential legal and societal issues, and what the pros and cons of generative AI are.

For more information see:

Attention is All You Need
arxiv.org/abs/1706.03762

Copilot
github.com/features/copilot

ChatGPT
openai.com/blog/chatgpt

Stable Diffusion
stability.ai/blog/stable-diffusion-public-release

Midjourney
midjourney.com

openVINO
intel.com/content/www/us/en/developer/tools/openvino-toolkit/overview.html

Intel Extension for PyTorch
intel.com/content/www/us/en/developer/tools/oneapi/extension-for-pytorch.html

oneAPI
intel.com/content/www/us/en/developer/tools/oneapi/overview.html

Tim Davis @ Texas A&M Github Copilot Tweet
twitter.com/DocSparse/status/1581461734665367554

ChatGPT Tech Radar Article
techradar.com/news/i-asked-chatgpt-to-write-about-itself-in-my-style-so-i-didnt-have-to

Guests
Ezequiel Lanza – Open Source, AI Evangelist @ Intel
Benjamin Consolvo – AI Community Manager @ Intel

Read/Download the transcript

Tags: AI, artificial intelligence, Benjamin Consolvo, ChatGPT, DALL-E, deep learning, developers, Ethical AI, Ezequiel Lanza, Generative AI, Midjourney, Open Source, OpenVINO, Stable diffusion, Transformers
 
Posted in: Artificial Intelligence, Code Together, Intel